ABSTRACT Reciprocal genomic disorders (RGDs) involve recurrent microdeletion and microduplicaton of identical genomic segments. RGDs are mediated by non-allelic homologous recombination (NAHR) and are collectively among the most common recurrent genetic causes of neurodevelopmental disorders (NDD) and congenital anomalies in humans. Given that the impact of RGDs is usually early in development, these disorders disproportionately affect children and often result in lifelong disabilities. Discovery of the genes the molecular consequences of RGDs and the genes that underlie components of these disorders would therefore represent exceptionally high priority targets for mechanistic studies and therapeutic targeting across a spectrum of Mendelian and complex disorders. Our Preliminary Data suggest that an integrated in vitro and in vivo molecular and computational genomics approach using cellular and animal modeling can identify molecular signatures associated with RGDs and the genetic drivers of aberrant phenotypes and dysregulated networks. In these studies, we will first define the gene expression profiles and cellular phenotypes associated with microdeletion and microduplication of the 8-12 most prevalent RGD regions in neural derivatives from isogenic induced pluripotent stem cell (iPSC) lines. We will accomplish this using a CRISPR/Cas9 genome editing approach we recently developed that targets the flanking segmental duplications and mimics NAHR-mediated mechanisms in humans (Aim 1). We will then seek the specific genes associated with RGD-associated phenotypes using high-throughput driver gene screening in zebrafish (Aim 2) to evaluate all individual genes and pairwise interactions within RGD regions. In Aim 3 we will then seek to validate these predicted drivers and determine their impact in diverse neuronal lineages and across mouse tissues. These studies will thus follow a framework our investigative team has previously used to identify genetic drivers of non-recurrent microdeletion syndromes and several RGD regions, including 16p11.2 RGD, and apply innovative approaches and technologies to enable us to conduct these studies at scale and compare signatures across RGDs. At their conclusion, tehse analyses will define the molecular signatures of the most common RGDs in humans, the genes that drive specific components of these signatures, their tissue specificity, and the capacity to rescue the strongest signatures through dosage manipulation in vitro and in vivo.